• 전자공학회논문지SC
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• 제41권3호
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• pp.39-46
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• 2004

본 논문은 IPMSM 드라이브의 고성능 속도 제어를 위하여 퍼지제어와 신경회로망을 혼합 구성한 적응 FNN 제어기를 제시한다. 적응 FNN 제어기는 기준 모델에 기초한 적응 메카니즘을 적용하여 신경회로망의 고도의 적응제어와 퍼지제어기의 강인성 제어의 장점들을 접목한다. 적응 FNN 제어기의 출력은 FNN 제어기의 출력과 적응 퍼지제어의 출력을 합하여 출력을 얻는다. 적응 FNN 제어기는 다양한 동작조건에서 응답특성을 분석하고 평가한다. 제시한 적응 FNN 제어기의 타당성은 IPMSM 드라이브 시스템에 적용하여 성능 결과로 입증한다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.3133-3141
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• 2011

The next generation domestic high speed railway system is a power distributed type and uses vector control method for motor speed control. Nowadays, inverter driven induction motor system is widely used. However, recently PMSM drives are deeply considered as a alternative candidate instead of an induction motor drive system due to their advantages in efficiency, noise reduction and maintenance. The next-generation high speed train is composed of 2 converter units, 4 inverter units, and 4 Traction Motor units. Each motor is connected to the inverter directly. In this paper, the effect of IPMSM parameter variations to the system operation characteristics of the multi inverter drive high speed train system are investigated. The parallel connected inverter input-output characteristics are analyzed to the parameter mismatches of IPMSM using the 1C1M control simulator based on Matlab/Simulink.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1009-1010
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• 2007

This paper presents Fuzzy-Neuro PI controller of IPMSM drive using fuzzy and neural-network. In general, PI controller in computer numerically controlled machine process fixed gain. To increase the robustness, fixed gain PI controller, Fuzzy-Neuro PI controller proposes a new method based fuzzy and neural-network. Fuzzy-Neuro PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 B
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• pp.731-732
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• 2006

The paper is proposed maximum torque control of IPMSM drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) and artificial neural network(ANN). For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN and ANN, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the ALM-FNN and ANN.

• 한국철도학회논문집
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• 제11권4호
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• pp.398-403
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• 2008

전동차용 견인전동기 시스템은 저항 및 쵸퍼 제어에 의한 직류 전동기 방식에서 인버터 제어에 의한 유도전동기 방식으로 발전하였다. 오늘날 유도전동기 기술은 어느 정도 성숙기에 접어들었지만 최근에는 소음제거, 효율 극대화 및 유지보수 비용 절감 등의 이점이 있는 감속기를 제거한 직접 구동용 영구자석 전동기가 새로이 각광받고 있다. 특히 기계적으로 견고한 매입형 영구자석 동기전동기는 출력/토크 밀도가 높고 약계자 제어성이 우수하며 고효율 운전이 가능하다. 본 논문은 자기적 포화특성이 심한 영구자석 전동기를 대상으로 고급화된 비선형 수치해석 기법을 적용하여 설계된 전동기의 특성해석을 나타낸다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.694_695
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• 2009

본 논문은 매입형 영구자석 동기 전동기(IPMSM)의 고속출력 구동을 위한 제어 특성 해석을 시뮬레이션을 통해 나타낸다. IPMSM의 d축,q축 인덕턴스인 Ld, Lq 선형모델과 비선형 모델의 선형 제어와 비선형제어를 실험과 시뮬레이션에 의하여 비교 분석 하였다. 본 논문은 IPMSM에 최적화된 제어 시스템 구연에 있어서 기초 자료가 될 것이다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2015년도 전력전자학술대회 논문집
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• pp.63-64
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• 2015

The control of IPMSM(Interior Permanent Magnet Synchronous Motor) for electric vehicle is important to track torque reference depended on accelerator. This paper executes IPMSM control applied the predictive current control which has good dynamic characteristic and, compare PI control with predictive current control to verify dynamic characteristic through simulation.

• 전력전자학회논문지
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• 제17권3호
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• pp.213-221
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• 2012

In a PWM inverter-fed IPMSM (Interior Permanent Magnet Synchronous Motor) drive, a dead time is inserted to prevent a breakdown of switching device caused by the short-circuit of DC link. This distorts the inverter output voltage resulting in a current distortion and torque ripple. In addition to the dead time, nonlinearity exists in switching devices of the PWM inverter, which is generally dependent on operating conditions such as the temperature, DC link voltage, and current. The voltage disturbance caused by the dead time and inverter nonlinearity directly influences on the inverter output performance, and it is known to be more severe at low speed. In this paper, a new compensation scheme for the dead time and inverter nonlinearity under the parameter variation is proposed for a PWM inverter-fed IPMSM drive. The overall system is implemented using DSP TMS320F28335 and the validity of the proposed algorithm is verified through the simulation and experiments.

• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.451-459
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• 2018

This work presents an approach for modeling of electric vehicle considering the vehicle dynamics, drive train, rotational wheel and load dynamics. The system is composed of IPMSM (Interior Permanent Magnet Synchronous Motor) coupled with the wheels through a drive train. Generally, IPMSM is controlled by ordinary PID controllers. Performance of the ordinary PID controller is not satisfactory owing to the difficulties of optimal gain selections. To overcome this problem, a new type of fuzzy logic gain tuner for PID controllers of IPMSM is required. Therefore, in this paper fuzzy logic based gain tuning method for PID controller is proposed and compared with some previous control techniques for the better performance of electric vehicle with an optimal balance of acceleration, speed, travelling range, improved controller quality and response. The model was developed in MATLAB/Simulink, simulations were carried out and results were observed. The simulation results have proved that the proposed control system works well to remove the transient oscillations and assure better system response in all conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.26-28
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• 2009

This paper proposes maximum torque control of IPMSM drive using adaptive teaming mechanism-fuzzy neural network (ALM-FNN) controller, model reference adaptive fuzzy tonal(MFC) and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using ALM-FNN, MFC and ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN, MFC and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, MFC and ANN controller.